Qualcomm teases what its Snapdragon 845 can do for VR

PostedFebruary 22, 2018

Here's what you need to know.

However, the Snapdragon 845 chipset isn't just bringing new features and a few technical improvements. Key benefits include Gigabit 4G LTE connectivity, near-instantaneous wake from sleep, background downloads, and "all-day" battery life.

With innovations around AI, Bluetooth audio and connected cars, there will be plenty on show, with a particular focus on the capabilities of the company's new flagship chipset, the Snapdragon 845, set to power the likes of the Samsung Galaxy S9. This provides Snapdragon 845 headsets with 30 percent faster graphics and 30 percent better power efficiency than Snapdragon 835 headsets, along with more than twice as much display throughput.

Qualcomm has also incorporated foveated rendering with its new headset, which uses an eye tracker to figure out where the user's eye is focused, and lower the resolution of the peripheral vision areas.

The new platform will also support what the company calls Roomscale tracking, using inside-out 6-DoF (degrees of freedom) tracking with SLAM (simultaneous localization and mapping) to follow your body and the room you're in.

A year ago at MWC, Qualcomm announced the reference design for the 835, then the product announcements came in the summer, and it hit the market afterward.

This is comprised of several hardware and software components to accelerate on-device AI-enabled user experiences. The AI Engine also comes with the Snapdragon Neural Processing Engine software framework, to help developers choose the optimal Snapdragon core for the desired user experience.

The Qualcomm AI Engine supports the Neural Processing Engine which includes support for both Google's Tensorflow and Facebook's Caffe and Caffe2 frameworks.

Support for the Android Neural Networks API, first released in Google's Android Oreo, gives developers access to Snapdragon platforms directly through the Android operating system.

Qualcomm said the AI Engine features have been used by Xiaomi, OnePlus, Vivo, Oppo, Motorola, Asus, ZTE, Nubia, Smartisan and Blackshark on devices. SenseTime and Face++ offer a variety of pre-trained neural networks for image and camera features including single camera bokeh, face unlock, and scene detection. Elliptic Labs' ultrasonic -based gesture controls use the AI Engine.

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